Fulfillment centers (FCs) encounter more than millions of products daily as they operate to fulfill consumer orders as soon as the orders are placed and enable shipping carriers to pick up shipments. Operations for managing inventory inside FCs may include ordering products and stocking the ordered products so the products can be shipped quickly as soon as the FCs receive the consumer orders. Although currently existing FCs and systems for inventory management in FCs are configured to forecast demands for products, a common issue arises when a FC runs out of stock by purchasing fewer products than an amount of consumer orders because of flawed predictions on product demand. For example, a consumer visits a website associated a merchant associated with an FC to purchase a desired product, but the consumer discovers that the desired product is out of stock. This leads to lost sales and poor customer satisfaction, and a review from the dissatisfied consumer may discourage potential sales from other buyers.
To mitigate such problems, conventional inventory management systems improve a prediction on demands of products by determining out of stock reasons. For example, the systems record one or more occurrences relating to an out of stock condition to determine a reason for the out of stock condition. While these systems attempt to determine out of stock reasons in an efficient manner, the process is manual and inconsistent.
Therefore, there is a need for improved methods and systems for predicting an out of stock item by determining a cause of out of stock condition.